Triple
T6629823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jonathan Lynn |
E149892
|
entity |
| Predicate | hasSpouse |
P13
|
FINISHED |
| Object |
Riva Richmond
Riva Richmond is a journalist and editor known for her work covering technology, business, and innovation.
|
E600976
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Riva Richmond | Statement: [Jonathan Lynn, hasSpouse, Riva Richmond]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Riva Richmond Context triple: [Jonathan Lynn, hasSpouse, Riva Richmond]
-
A.
Elizabeth Seaport
Elizabeth Seaport is a major commercial shipping and container terminal complex located in Elizabeth, New Jersey, forming part of the Port of New York and New Jersey.
-
B.
Marina
Marina is a recurring comedic character in the long-running British sitcom "Last of the Summer Wine," known for her flirtatious relationship with the married Howard.
-
C.
Marina
Marina is the given name of Marina von Neumann Whitman, an American economist and former General Motors executive.
-
D.
Marina
Marina is a female given name of Latin origin, commonly used in various cultures and often associated with the sea.
-
E.
Henrietta
Henrietta is a suburban community in western New York State, located near Rochester within the Rust Belt region along the Interstate 90 corridor.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Riva Richmond Triple: [Jonathan Lynn, hasSpouse, Riva Richmond]
Generated description
Riva Richmond is a journalist and editor known for her work covering technology, business, and innovation.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Riva Richmond Target entity description: Riva Richmond is a journalist and editor known for her work covering technology, business, and innovation.
-
A.
Elizabeth Seaport
Elizabeth Seaport is a major commercial shipping and container terminal complex located in Elizabeth, New Jersey, forming part of the Port of New York and New Jersey.
-
B.
Marina
Marina is a recurring comedic character in the long-running British sitcom "Last of the Summer Wine," known for her flirtatious relationship with the married Howard.
-
C.
Marina
Marina is the given name of Marina von Neumann Whitman, an American economist and former General Motors executive.
-
D.
Marina
Marina is a female given name of Latin origin, commonly used in various cultures and often associated with the sea.
-
E.
Henrietta
Henrietta is a suburban community in western New York State, located near Rochester within the Rust Belt region along the Interstate 90 corridor.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c687ee50048190aa151765bef16193 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6afa5c9b48190b645be96d446d0ca |
completed | March 27, 2026, 4:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6cbeb04348190957b8e5f098b72bf |
completed | March 27, 2026, 6:26 p.m. |
| NEDg | Description generation | batch_69c6cd0a98908190a5725c49bad7589d |
completed | March 27, 2026, 6:31 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6cdcf14508190876faa73f5eec884 |
completed | March 27, 2026, 6:34 p.m. |
Created at: March 27, 2026, 1:59 p.m.